Shonan Rotation Averaging: Global Optimality by Surfing SO(p) <sup>n</sup>
© 2020, Springer Nature Switzerland AG. Shonan Rotation Averaging is a fast, simple, and elegant rotation averaging algorithm that is guaranteed to recover globally optimal solutions under mild assumptions on the measurement noise. Our method employs semidefinite relaxation in order to recover prova...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Springer International Publishing
2021
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| Online Access: | https://hdl.handle.net/1721.1/137280 |
| _version_ | 1811081958001737728 |
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| author | Dellaert, Frank Rosen, David Matthew Wu, Jing Mahony, Robert Carlone, Luca |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Dellaert, Frank Rosen, David Matthew Wu, Jing Mahony, Robert Carlone, Luca |
| author_sort | Dellaert, Frank |
| collection | MIT |
| description | © 2020, Springer Nature Switzerland AG. Shonan Rotation Averaging is a fast, simple, and elegant rotation averaging algorithm that is guaranteed to recover globally optimal solutions under mild assumptions on the measurement noise. Our method employs semidefinite relaxation in order to recover provably globally optimal solutions of the rotation averaging problem. In contrast to prior work, we show how to solve large-scale instances of these relaxations using manifold minimization on (only slightly) higher-dimensional rotation manifolds, re-using existing high-performance (but local) structure-from-motion pipelines. Our method thus preserves the speed and scalability of current SFM methods, while recovering globally optimal solutions. |
| first_indexed | 2024-09-23T11:54:48Z |
| format | Article |
| id | mit-1721.1/137280 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:54:48Z |
| publishDate | 2021 |
| publisher | Springer International Publishing |
| record_format | dspace |
| spelling | mit-1721.1/1372802022-09-27T22:48:53Z Shonan Rotation Averaging: Global Optimality by Surfing SO(p) <sup>n</sup> Dellaert, Frank Rosen, David Matthew Wu, Jing Mahony, Robert Carlone, Luca Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Laboratory for Information and Decision Systems Massachusetts Institute of Technology. Department of Aeronautics and Astronautics © 2020, Springer Nature Switzerland AG. Shonan Rotation Averaging is a fast, simple, and elegant rotation averaging algorithm that is guaranteed to recover globally optimal solutions under mild assumptions on the measurement noise. Our method employs semidefinite relaxation in order to recover provably globally optimal solutions of the rotation averaging problem. In contrast to prior work, we show how to solve large-scale instances of these relaxations using manifold minimization on (only slightly) higher-dimensional rotation manifolds, re-using existing high-performance (but local) structure-from-motion pipelines. Our method thus preserves the speed and scalability of current SFM methods, while recovering globally optimal solutions. 2021-11-03T18:07:59Z 2021-11-03T18:07:59Z 2020-11 2021-04-16T17:47:50Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/137280 Dellaert, Frank, Rosen, David Matthew, Wu, Jing, Mahony, Robert and Carlone, Luca. 2020. "Shonan Rotation Averaging: Global Optimality by Surfing SO(p) <sup>n</sup>." Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12351 LNCS. en http://dx.doi.org/10.1007/978-3-030-58539-6_18 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Springer International Publishing arXiv |
| spellingShingle | Dellaert, Frank Rosen, David Matthew Wu, Jing Mahony, Robert Carlone, Luca Shonan Rotation Averaging: Global Optimality by Surfing SO(p) <sup>n</sup> |
| title | Shonan Rotation Averaging: Global Optimality by Surfing SO(p) <sup>n</sup> |
| title_full | Shonan Rotation Averaging: Global Optimality by Surfing SO(p) <sup>n</sup> |
| title_fullStr | Shonan Rotation Averaging: Global Optimality by Surfing SO(p) <sup>n</sup> |
| title_full_unstemmed | Shonan Rotation Averaging: Global Optimality by Surfing SO(p) <sup>n</sup> |
| title_short | Shonan Rotation Averaging: Global Optimality by Surfing SO(p) <sup>n</sup> |
| title_sort | shonan rotation averaging global optimality by surfing so p sup n sup |
| url | https://hdl.handle.net/1721.1/137280 |
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